Gangadharan Esakki, is a PhD student working towards his dissertation in the Department of Electrical & Computer Engineering (ECE) with a focus on Video compression standards (H.265/HEVC, x265, VP9), Adaptive real-time video communications and CODEC computational complexity in an optimization framework called DRASTIC (Dynamically Reconfigurable Architecture for Time-varying Imaging Constraints) funded by National Science Foundation grant. Prior to joining UNM, he received his Bachelor’s in Electronics & Communication Engineering with Distinction from Anna University in 2009 and his M.S. in Computer Engineering from UNM in 2014. Currently advised by Dr. Marios Pattichis at ivPCL (image and video Processing and Communications laboratory), his work is mostly based on developing optimization algorithms for real-time video encoding, camera motion activities, and complexity analysis. His other research interests include H.264/AVC, Machine learning, Computer vision, Statistics and Mathematical models.
He recently presented his research paper titled, Adaptive High Efficiency Video coding based on Camera Activity Classification at the 27th Data Compression Conference in Utah, one of the top conferences in the video coding/compression field. In 2016 while interning in Intel, he worked with Intel Real-Sense camera and contributed to the prototype models as part of the PERC (Perceptual Computing) group. Also, his research was supported with 2 patents that are covered under his NSF grant that won the UNM STC Innovation Award. Additionally, he has served on several student based associations at UNM including: the Graduate & Professional Student Association (GPSA 2015-2016) as a Council representative, the World Student Alliance (WSA 2013-2014) as a committee member, and the Indian Student Association (ISA 2012-2013) as Treasurer. Besides school, he enjoys his cup of cappuccino, writes blogs, teach/practice yoga, climb mountains, ski and volunteering for community service.